Publications
NIBIOs employees contribute to several hundred scientific articles and research reports every year. You can browse or search in our collection which contains references and links to these publications as well as other research and dissemination activities. The collection is continously updated with new and historical material.
2017
Abstract
No abstract has been registered
Authors
Johannes M. Baveco Anne Kari Bergjord Olsen Jarle W. Bjerke Magda E. Chudzinska Loïc Pellissier Caroline E. Simonsen Jesper Madsen Ingunn Tombre Bart A. NoletAbstract
Many goose species feed on agricultural land, and with growing goose numbers, conflicts with agriculture are increasing. One possible solution is to designate refuge areas where farmers are paid to leave geese undisturbed. Here, we present a generic modelling tool that can be used to designate the best locations for refuges and to gauge the area needed to accommodate the geese. With a species distribution model, locations are ranked according to goose suitability. The size of the area to be designated as refuge can be chosen by including more or less suitable locations. A resource depletion model is then used to estimate whether enough resources are available within the designated refuge to accommodate all geese, taking into account the dynamics of food resources, including depletion by geese. We illustrate this with the management scheme for pink-footed goose Anser brachyrhynchus implemented in Norway. Here, all geese can be accommodated, but damage levels appear to depend on weather, land use and refuge size.
Abstract
1.A large population increase of the Svalbard-breeding pink-footed goose Anser brachyrhynchus over recent decades has intensified the conflict with agriculture at the spring-staging sites in Norway. Knowledge of the yield loss caused by goose grazing in these northern areas is lacking, and the motivation behind the study was to quantify a relationship between grazing pressure and yield loss of agricultural grasslands and corresponding changes in vegetation composition. 2.Field trials were established on agricultural grasslands at four sites in central Norway. Eight plots were established at each site; four with exclosures to exclude or reduce grazing from geese and four with access for the geese. The exact same plots were followed for 2–4 years. Dropping density, used as a measure of grazing pressure, and compressed sward height were recorded throughout the goose staging periods, and dry matter yield was determined at first and second harvests. Plant samples from first harvests were analysed for vegetation composition. 3.Grazing pressure varied between both years and sites. Exclosures reduced grazing pressure by 75–78% during high-pressure grazing periods and increased first harvest yields by up to 31%. At lower grazing pressure, exclosures prevented grazing completely. Grazing pressure was inversely correlated with dry matter yield at first harvest, but second harvest yields were unaffected. 4.The fraction of sown species declined while the fraction of weeds increased during the study both in open plots and exclosures, but level of grazing pressure did not have any significant influence on the overall fraction of sown species, or in any specific year. 5.Synthesis and applications. As the same plots were measured over several years, it was possible to quantify goose-grazing effects beyond one season. In the context of the wildlife-agriculture conflict, the results demonstrate that some farmers always suffer disproportionately with yearly variations. The relationship between grazing pressure and yield loss may provide knowledge to a regional goose grazing subsidy scheme in the study area, identifying the most affected areas and distributing the subsidies correspondingly. However, the seasonal variations in grazing pressure demonstrate the difficulty of targeting exact areas on a yearly basis. On the other hand, the observed variations may promote another management tool in the form of delayed ploughing of stubble fields before spring sowing, as stubble fields may attract more geese, reducing the grazing pressure on agricultural grasslands and hence the overall conflicts with agricultural interests.
Abstract
No abstract has been registered
Authors
Till SeehusenAbstract
No abstract has been registered
Authors
Wendy Marie WaalenAbstract
No abstract has been registered
Abstract
Different sowing methods and sowing rates were evaluated in organic seed production of timothy (two trials), meadow fescue (two trials) and red clover (one trial) in Southeast Norway, during 2010–2013. The plan included: (1) broadcast sowing of grass/clover, cover crop sown at 12 cm row distance; (2) sowing of cover and seed crop in crossed rows, both at 12 cm row distance; and (3) sowing of cover crop and seed crop in every other row. The three sowing rates were 5, 10 and 15 kg ha−1 in timothy and meadow fescue and 3, 6 and 9 kg ha−1 in red clover. On average for sowing rates and all trials with timothy, meadow fescue and red clover, first year’s seed yields were 5–6%, 20–25% and 19–25% higher on plots sown with cover crop and seed crop in every other row than on plots where seed crop had been broadcast or sown perpendicularly to the cover crop. The different sowing methods had no effect on weed coverage or weed contamination in the cleaned seed. Increasing sowing rate usually had a negative influence on seed yield, while weed coverage/contamination was not significantly affected. It is concluded that organic seed crops should be established with cover crop and seed crop in every other row at a low sowing rate. However, in an organic production system, even this favorable method will not always be sufficient to meet the requirement for seed crop purity.
Authors
Lars T. HavstadAbstract
No abstract has been registered
Authors
Unni AbrahamsenAbstract
No abstract has been registered
Abstract
Based on soil temperature, snow depth and the grown cultivar's maximum attainable level of frost tolerance (LT50c), the FROSTOL model simulates development of frost tolerance (LT50) and winter damage, thereby enabling risk calculations for winter wheat survival. To explore the accuracy of this model, four winter wheat cultivars were sown in a field experiment in Uppsala, Sweden in 2013 and 2014. The LT50 was determined by tests of frost tolerance in November, and the cultivars’ LT50c was estimated. Further, recorded winter survival from 20 winter wheat field variety trials in Sweden and Norway was collected from two winter seasons with substantial winter damages. FROSTOL simulations were run for selected cultivars at each location. According to percentage of winter damage, the cultivar survival was classified as “survived,” “intermediate” or “killed.” Mean correspondence between recorded and simulated class of winter survival was 75% and 37% for the locations in Sweden and Norway, respectively. Stress factors that were not accounted for in FROSTOL might explain the poorer accuracy at the Norwegian locations. The accuracy was poorest for cultivars with intermediate LT50c levels. When low temperature was the main cause of damage, as at the Swedish locations, the model accuracy was satisfying.